Strategic insights from complex, high-dimensional healthcare data, fostering integrated analytics and strengthening the organization’s competitive edge in precision medicine.
- Integrating AI and decision science to design faster, smarter, lower-risk trials
- Using adaptive methods to boost efficiency and responsiveness in trial design
- Turning complex data into insights that accelerate timelines and improve outcomes
Tom Oliver
Head of Product
Faculty
Tom Oliver is Head of Product at Faculty, where he leads the strategy and roadmap for Faculty Frontier™, the company’s decision-intelligence platform that helps enterprises operationalize AI in day-to-day decisions. Tom partners with executives and cross functional teams, including product managers, engineers, data scientists, and designers, to discover, build, and scale products that solve real problems for technical and business users. He collaborates closely with Faculty’s leadership and with key stakeholders and clients across pharma, retail, consumer goods, and healthcare, turning complex challenges into measurable outcomes. Before joining Faculty, Tom held leadership positions at PwC, focusing on technology enabled transformation, operating model change, and enterprise technology selection and deployment. His public writing explores the future of work, AI ethics, and human centric design, asking how powerful systems can advance human flourishing, not only efficiency. He holds a degree from the University of Oxford.
Tarun Walia
Senior Director, Decision Science
Novo Nordisk
Stephanie Vakaljan
Director of Trial Analytics and Decision Support
GSK
Faculty
Website: https://faculty.ai/
Founded in 2014, Faculty is one of Europe’s leading applied AI companies. Our suite of AI services and products helps organisations design, build, and deploy high-performing AI solutions that deliver measurable impact for their frontline teams. Faculty is also the developer of Faculty Frontier™, a Decision Intelligence platform used by leading pharmaceutical companies to transform decision-making at scale.
Widely recognised as a leader in AI safety, we work closely with the world’s top AI labs, such as OpenAI and Anthropic, to ensure their latest models are safe, human-led, and explainable. Our expertise spans advising Boards, leadership teams, and governments on AI strategy; delivering AI systems that improve critical public services and business outcomes; and equipping organisations with the knowledge and skills they need to thrive in the AI era.
Our PhD-heavy team has delivered hundreds of real-world AI projects across every sector of the economy. Headquartered in London, Faculty remains founder-led and has raised over £40m from investors including The Apax Digital Fund, LocalGlobe, and GMG Ventures.
Learn how AI models enhance physics-based simulations to predict molecular interactions and optimize drug design.
Discover the synergy between machine learning and classical methods to accelerate screening and improve the accuracy of drug discovery.
Sreyoshi Sur
Former Scientist, Molecular Engineering & Modeling
Moderna
Explore how AI enhances biomarker discovery by analyzing large datasets to uncover novel biomarkers for disease diagnosis and therapeutic efficacy.
Learn how integrating digital biomarkers with AI improves the interpretation of data from wearable devices and traditional lab-based biomarkers for better patient stratification and treatment personalization.
Moderator
Nikolaos Patsopoulos
Biomarker Development Therapeutic Area Lead
Novartis Institutes for BioMedical Research (NIBR)
Satarupa Mukherjee
R&D Leader, AI/ML (Digital Pathology)
Roche
Jack Geremia
CEO
Matterworks
Virginia Savova
Senior Director, Head Cell-Targeted Precision Medicine
AstraZeneca
Matterworks
Website: https://www.matterworks.ai/
Matterworks is unlocking predictive biology through an AI-powered platform that immediately uncovers actionable discoveries hidden in LC-MS raw data. Our Large Spectral Model (LSM) has been trained on billions of proprietary raw LC-MS spectra across diverse applications. Built on this foundation, the Pyxis query system leverages the LSM to rapidly identify biomolecules without disparate, time-consuming, and laborious downstream processes.
Available in application-specific configurations, Pyxis transforms conventional manual processing into immediate AI-driven results, expanding the breadth and speed of biomarker discovery, upstream bioprocess optimization, and downstream process development.
Matterworks brings together expertise in AI, software engineering, and analytical chemistry to bridge the gap between raw data and phenotypic endpoints hidden in the dark matter. By developing our AI-powered platform for rapid biomolecule discovery, identification, and concentration determination, we are creating the new standard for researchers, data scientists, and industry leaders to uncover previously unattainable insights and accelerate decision-making across discovery and development.
Examine how AI models are being developed, validated, and governed to meet regulatory expectations, with practical insights into documentation, auditability, and lifecycle management to ensure safe, transparent, and compliant deployment in GxP environments.
Benjamin Stevens
Director, CMC Policy
GSK
Guides strategic IT decisions by clarifying trade-offs between cloud and on-premise solutions, to align infrastructure strategy with agility, security, and compliance objectives.
Explore practical strategies for scaling AI implementation across clinical development pipelines, enabling faster trial execution, smarter protocol design, and improved patient recruitment while aligning with evolving regulatory expectations.
Maria Florez
Senior Consultant
Tufts
- Explore how AI models predict protein 3D structures from sequences, enabling insights into folding pathways and functional conformations
- Examine foundational models that reveal protein–protein interactions and guide design of innovative drug candidates
Miles Congreve
Chief Scientific Officer
Isomorphic Labs
Learn how AI-driven approaches integrate multiomics data, including genomics, proteomics, and transcriptomics, to identify potential drug targets and disease biomarkers for complex diseases.
Explore how AI models synthesize cross-omic data and real-time multiomic information to uncover novel biological mechanisms, identify potential biomarkers and enable precision medicine.
Moderator
Eva Fast
Senior Principal Computational Biologist
Pfizer
Kiran Nistala
Head, Functional Genomics
Alkermes
Harris Bell-Temin
Director, Proteomics
Johnson & Johnson Innovative Medicine
Moderator
David Champagne
Senior Partner
McKinsey & Company
Melissa Landon
Head, Commercial & Business Development, AI & Automation
MilliporeSigma
David Hallett
Chief Scientific Officer
Recursion
Morten Sogaard
Senior Vice President & Head, Astellas Innovation Lab
Astellas Pharma
Peter Clark
Vice President, Digital Chemistry & Design
Novo Nordisk RDUS
MilliporeSigma
Website: https://www.sigmaaldrich.com
Together with our colleagues, customers and stakeholders, we impact life and health with science. Before researchers can make scientific breakthroughs, they must have access to state-of-the-art tools, services and expertise to perform experiments and engineer new products. That’s where we come in.
We offer one of the broadest portfolios in the industry for scientists, best-in-class products for pharmaceutical development and manufacturing, and a fully integrated service organization to support CDMO and contract testing across traditional and novel modalities.
Our vision is a world where our innovative products, services and digital offerings help create solutions for people globally and a sustainable future for generations to come.
The life science business of Merck KGaA, Darmstadt, Germany, operates as MilliporeSigma in the US and Canada. Merck KGaA, Darmstadt, Germany is a global science and technology company with around 60,000 employees in more than 66 countries.